Machine Learning Engineer

Machine learning engineers build computer systems that learn from data and get better over time. They write code and test models that help businesses make predictions, spot patterns, and automate decisions - from spotting fraud to recommending films.

Machine Learning Engineer

28

Computer Science

AI IMPACT
AI CAN DO28%moving to90%
THE DOOR, NOWC
THE DOOR, 20 YRSD
STARTING PAY£30,000 - £40,000
NO MOATNo physical, legal or personal barrier protects this work from software.
AI helps here, but has not taken over
AI can already do some of this job, but the day-to-day work still leans on a person to decide, check and take responsibility. Nothing formally protects this job though, so the safest move is to keep building the judgement AI cannot yet copy.

Career progression path

1FIRST STEPJunior Machine Learning EngineerIn this entry-level role, you will assist in developing machine learning models and gain hands-on experience with data preprocessing and algorithm implementation.£30,000 - £40,000
2GAINING EXPERIENCEMid-level Machine Learning EngineerAs a mid-level engineer, you will take on more complex projects, lead small teams, and contribute to the strategic direction of machine learning initiatives.£50,000 - £70,000
3PEAK CAREERSenior Machine Learning EngineerIn this peak career stage, you will lead large-scale machine learning projects, mentor junior engineers, and drive innovation within your organisation.£80,000+

Real apprenticeship standards

Live UK apprenticeship standards that lead into this career, from the Institute for Apprenticeships register.

L6Machine learning engineer24 months typicalnot published
There is more than one way in

You do not have to go the university route to get here. There is also a vocational route that skips a degree entirely.

Careermash

Careermash: navigate your career path with real data. Explore career profiles, salary benchmarks, AI impact forecasts, and the qualifications you need to get there.


AI EXPOSURE = the share of a job's day-to-day tasks AI can already do today, from the same exposure engine used across this site (Anthropic labour market research, 2026, observed real-world AI usage by occupation). Higher means more exposed. It is a measurement of now, not a prediction. THE DOOR = how hard the job is to get into, grade A (easy) to E (extremely hard), from each career's published forecast (OpenAI, "The AI Jobs Transition Framework", Richmond 2026, CC BY 4.0). A card marked MOAT NOT YET CLASSIFIED has a real exposure score but no entry yet in our moat register, so we make no claim about what structurally protects it. Scorecard grades and verdicts are Careermash editorial judgment: we show forecasts as forecasts and own our conclusions. Salary and pathway figures are each career's own published profile. Careermash is a service provided by What School Ltd.

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